A reliable source of electricity is essential for almost all aspects of modern life.
Providing reliable electricity is, at present, an enormously complex technical challenge. It involves real-time assessment and control of an electricity system consisting of generation, of all types (nuclear, coal, oil, natural gas, hydro power, geothermal, photovoltaic, etc.), and load e.g. the appliances, instruments etc. using the electricity.
The electricity is supplied over a distribution network consisting of transmission lines interconnected by switching stations. The generated electricity is generally ‘stepped-up’ by transformers to high voltages (230-765 kV) to reduce transmission losses of electricity (through heating). The generators, distribution networks and loads comprise an electricity power grid.
Reliable operation of a power grid is complex as, at present, electricity must be produced the instant it is used, meaning power generation and demand must be balanced continuously. In existing power management systems, the supply of electricity is balanced to demand by planning, controlling and coordinating the generation of electricity.
Failure to match generation to demand causes the frequency of an AC power system to increase when generation exceeds demand and decrease when generation is less than demand.
In the UK, the electricity boards must maintain a nominal frequency of 50 Hz and are allowed a variation of ±½%. In the US, this nominal frequency is 60 Hz. In some closed loop systems, such as an airplane, the nominal frequency is 400 Hz. The nominal frequency is the frequency of the AC power that a grid was designed for and it is intended to keep this frequency controlled and stable.
Random, small variations in frequency are normal, as loads come on and off and generators modify their output to follow the demand changes. However, large deviations in frequency can cause the rotational speed of generators to move beyond tolerance limits, which can damage generator turbines and other equipment.
The variation in frequency can also damage loads.
A frequency change of just ±½% is a large signal in terms of the precision of modern semiconductor instrumentation.
There are problems with the present supply-side style architecture of matching generation to demand. At present, when extreme low-frequencies can not be dealt with, i.e. demand out-strips generation, automatic under-frequency load shedding may be triggered, which takes blocks of customers off-line in order to prevent a total collapse of the electricity system. This may have the effect of stabilizing the system, but is extremely inconvenient and even hazardous to the user.
After a blackout the grid is at a particularly sensitive stage and recovery is slow. Large generators generally require other generators to make some power available to start or re-start it. If no power is available, such generator(s) cannot start. So grid systems have services, known as “black start” services, whereby a subset of generation has the capacity to start and continue generating, even when the rest of the grid is inactive (i.e. black). Grid operators have prepared planned sequences for restoring generation and load. These ensure that the limited initial supplies are used first to provide communication and control, then to start up bigger generators, and thereafter the load is progressively connected to match the increasing availability of generation.
The entire process of black start is a fraught one. A blackout is a very rare event, and not one that can be practiced except in an actual crisis. Everybody involved is under severe pressure, and the systems are being operated quite outside their normal operating range (and sometimes outside their design range). Every step when load or generation is added is a shock to the system and the grid can take seconds or minutes to stabilize after it happens. Prudence would suggest making changes in small increments. This inevitably slows down the overall process, prolonging the blackout for those who are still to be reconnected.
In order to insure as much as possible against load-shedding, a power system will be operated at all times to be able to cope with the loss of the most important generator or transmission facility (i.e. the most significant single contingency). Thus, the grid is normally being operated well below its capacity such that a large random failure does not jeopardize the system as a whole. This, however, means that the generation is not operating as efficiently as possible, with a resulting increase in electricity supply costs.
High air conditioning and other cooling loads in the summer and high space heating loads in the winter are a normal cause of peak-loads. Grid operators, however, use rigorous planning and operating studies, including long-term assessments, year-ahead, season-ahead, week-ahead, day-ahead, hour-ahead and real time operational contingency analyses to anticipate problems.
The unexpected can still occur, which is why the system operates with headroom for compensating for the largest contingency. Utilities can use additional peaking generators, which have high running cost, to provide additional electricity when needed or, alternatively do not operate main generators at capacity so as to leave some potential for extra generation to satisfy excess loads. Both of these methods result in a higher unit cost of electricity than if the system was operating nearer to capacity.
There has been proposed an alternative architecture for matching load and generation to that presently used. The general idea is to compensate for differences between load and generation using the demand-side by way of load management.
Limited literature exists on the concept of using load, or demand, to contribute (at least) to grid stability.
U.S. Pat. No. 4,317,049 (Schweppe et al.) proposes such a different basic philosophy to existing electric power management in which both supply and demand of electricity respond to each other and try to maintain a state of equilibrium.
This document identifies two classes of usage devices. The first type are energy type usage devices characterized by a need for a certain amount of energy over a period of time in order to fulfil their function and an indifference to the exact time at which the energy is furnished. Examples were space conditioning apparatus, water heaters, refrigerators, air compressors, pumps, etc. The second class was a power type usage device characterized by needing power at a specific time. Such devices would not be able to (fully) fulfil their function if the power was not supplied at a designated time and rate. Examples include lighting, computers, TVs, etc.
The Frequency Adaptive, Power-Energy Re-scheduler (FAPER) of the Schweppe et al. patent provided its power management by application of a FAPER to energy type usage devices. The Schweppe et al. patent particularly discusses application of the FAPER to a water pump for pumping water into a storage tank.
The water level in the water tank has a minimum allowable level Ymin and a maximum allowable level Ymax. Ordinarily, the water pump will be switched on to pump water into the storage tank when the level falls to or below the minimum level and turns the pump off when the maximum level is reached. Otherwise, the pump is idle.
The FAPER modifies these limits (Ymax, Ymin) depending upon the system frequency. Thus, in a period of high frequency (electricity demand shortage), i.e. when the grid frequency increases above nominal, the minimum water level causing the pump to activate (Ymin) is increased and the maximum water level (Ymax)) is also raised. Thus, the pump switches on at a higher level and stops at a higher level than operation not under the control of a FAPER. This means that the excess in generation is being taken up. Using the same principle, as the electricity frequency drops below the grid nominal frequency (a generation shortage), the minimum and maximum water levels are lowered. This lowering results in ON pumps being switched off sooner and OFF pumps coming on later than usual, and so using less electricity, thereby reducing the load.
According to Schweppe, the raising of the limits (particularly the maximum) and the lowering of the limits (particularly the minimum) should have an extent cap, defined by either user desires or safety requirements. Thus, the limits should be extendable, but only to a certain extent, as otherwise the tank could unacceptably empty or overflow.
The broad concept uncovered by Schweppe in this patent is that consuming devices, which incorporate some sort of energy store and operate to a duty cycle, are useful in providing grid responsive behavior. When running, the energy store is being replenished or filled and, thus, the potential energy of the store is increasing. When the devices are not running, their function is preserved because of the load's ability to store energy.
The FAPER modifies the timing of the load's consumption, without detriment to the service provided by the device, using the grid frequency as a guide. Thus, the potential energy of the device is increased when the grid frequency is high in order to maximize the amount of energy fed into the device which is stored. This compensates for any excess. During times of insufficient generation (high frequency), the potential energy of the device is lowered, thereby releasing energy to the grid and compensating for the shortage.
Moving on from the FAPER, a different and improved “responsive load system” was disclosed in GB 2361118 by the present inventor. The responsive load system was based on the same underlying principle as the FAPER devices, that grid stability can be at least aided by using demand-side grid response, and built on the response method and offered a further enhancement of using probabilistic methods as to the ON/OFF switching timing for the load.
One problem with the FAPER device is that, without any randomization, the smallest movement of the frequency could result in all loads with FAPERs applied responding in the same way and doing so simultaneously. This could result in a destabilizing influence on the grid. A more gradual response is needed and the responsive load system offered this by distributing the frequencies to which each device is responsive by using a randomized function.
As mentioned above, the responsive load system of GB 2361118 defines a probability based method for choosing the frequency to which a device is sensitive. In this way, a progressively larger proportion of the responsive load device population changes the load as the system frequency departs from the nominal frequency of the grid.
In more detail, the responsive load system uses a randomizer to choose both a high frequency and a low frequency to which the device is sensitive. This is advantageous over the FAPER device as more and more load is switched on or off progressively as the frequency increases or decreases, respectively.
The random inputs for the high and low frequencies to which the devices are sensitive are revised from time to time. This step has the advantage of distributing any disadvantages of responsive devices among the population and ensuring that no one device was stuck with unfavorable frequency triggers. For example, it would not be appropriate if a particular device was constantly sensitive to the slightest change in frequency whereas another device had such broad trigger frequencies that it only provided frequency response in extreme grid stress situations.
One problem with this system is that the controller is not tamperproof. Users, such as users of air conditioning, might choose to turn up their controls because of the slight heating/cooling of a room beyond that desired as a result of a frequency responsive load change being noticed. Thus, if the air conditioner is generating in a lower temperature range, that is the air conditioner is working harder and is on more frequently, because of an increase in grid frequency, and a user notices this and turns the air conditioning down, before the frequency returns to an acceptable level, then the response has been lost.
Partially because of the above problem, the Grid Stability System of UK patent application number 0322278.3 was formed. The grid stability system prevents an end user from overriding the frequency response function by fixing the frequency triggers at pre-grid stress settings. In this way, manipulation of a set point controller, such as a thermostat, is made ineffective for the duration of the period of high stress.
The grid stability system also defines three states of the system, normal, stress and crisis. The stress level of the grid determines which of the above three grid states are relevant.
The stress level of the grid can be determined by comparing the present grid frequency to limit values for the frequency and determining whether the current frequency falls inside limits chosen to represent a normal state, a stressed state or a crisis state.
Rapid changes in frequency, whatever their absolute value, are also used as indicators of grid stress level by defining limits for the rate of change of the grid frequency.
The grid stress level can also be indicated by an integration, over time, of the deviation of the grid frequency from the nominal grid frequency. Thus, even if the extent of frequency departure is very small, if it departs for a long enough time, then a grid stress or crisis condition is still determined.
The grid status is, therefore, determined, according to the grid stability system, by taking into account instantaneous large frequency departures from nominal, rapid changes of frequency and accumulatively large, but not necessarily outside a preferred frequency change at any given time, departures all being signs of grid stress. Each of these possible types of grid indicators has an associated set of limits that individually or in combination determine whether the grid is in a normal state, a stressed state or a crisis state.
Having determined the status of the grid, that is whether the grid is in a normal state, a stressed state or a crisis state, the controller of the grid stabilizing system adapts its grid responsive behavior depending upon the determined grid status. If a normal status is determined, the device provides response to frequency changes in the same way as the original responsive load device. So, as grid frequency rises above the temperature determining trigger frequency, off devices will switch on in order to “take up” the extra generation. In the case that the grid frequency falls below a low frequency trigger value, “on” devices will switch off to reduce the load upon the grid.
If operated according to the FAPER invention, a physical variable associated with the load (water level, temperature) is still controlled within minimum and maximum values during this time, but the limits are extended so that devices switched on and devices already on will stay on for longer than if the controlled device was operating within the normal frequency limits. Similarly, in periods of overly high grid frequency, off devices will stay off for longer as the lower limit of the physical variable has been extended as well.
Using the example of the water tank, as grid frequency increases above the higher frequency limits, off devices will switch on and on devices will stay on until the physical variable reaches its extended limit or until the frequency returns below the higher frequency limits. If the normal range for the water tank depth lies between 1 and 1.5 meters, for example, if the grid frequency rises above the higher frequency limits, off devices will switch on and on devices will stay on up to an extended water depth of 1.7 meters, for example. Thus, the potential maximum level of the water tank has been raised above its normal level. Further, the potential energy of a population of water pumps controlled in this way will have increased their average depth of water. This serves to compensate the excessive generation, which produced the high grid frequency, and stored the excessive grid energy, which will compensate, to some extent, the higher frequency. When the frequency drops below the lower frequency limits, this energy is repaid to the grid by switching on devices off and keeping off devices off up to a lower extended physical variable limit of, for example, 0.8 meters. This allows a large population of devices to reduce their potential energy and supply the energy difference into the grid. This serves to compensate for the lack of generation that resulted in the low frequency.
If operated according to the responsive load system of GB2361118, the control limits remained unchanged, but the device could be switched on or off if the system frequency moved beyond the frequency to which the device was sensitive. So the device could be switched before it reached its control limits, and this extra switching modified the load and so contributed the change of load necessary to balance the system.
Using the example of the water tank again, low frequency would cause an on device to switch off at, for example, 1.4 m and so earlier than if the limit of 1.5 m was reached, and, conversely, high frequency would cause the device to switch on at, for example, 1.1 m and so earlier than if the lower limit of 1 meter was reached.
Together, these cause the average water level in a population of devices to become lower when the frequency is low, and to become higher when the frequency was high, although each individual device would operate within its control limits.
The frequency limits for a particular device are chosen to fall within an upper frequency range and a lower frequency range. As with the Responsive Load previously discussed, a randomizer is used to choose the particular high trigger frequency and the particular low trigger frequency such that a population of devices have high trigger frequencies and low trigger frequencies distributed within the upper frequency range and the lower frequency range, respectively. Thus, a window is provided between the distribution of high trigger frequencies and low trigger frequencies. This window is centered around the nominal frequency. The window allows the controlled load, e.g. a water tank, refrigerator or air conditioner, to operate entirely as normal, i.e. as though it did not have a frequency responsive controller applied to it, when the frequency of the grid is close enough to the nominal grid frequency to lie within the window. Response is provided only when the grid frequency extends outside this window.
In the case that a stressed state is determined, the control limits of the device are frozen at pre-stress settings so that manipulation of a control panel to adjust a set point for the sensed physical variable (e.g. temperature) is ineffective. Thus, the user of the controlled load cannot adjust the loads settings, for example by using a thermostat control. If the responsive device is controlling an air conditioner, a grid responsive induced change in room temperature could be noticed. A user may decide to attempt to counter the change in temperature by adjusting the thermostat. The responsive load device of the grid stabilizing system overrides such an adjustment of the set point when the grid is determined to be in a stressed condition. This is important as the grid is particularly sensitive during a period of grid stress and users negating the response provided could worsen the destabilization of the grid.
In extreme circumstances, when a risk of blackout exists, a grid crisis state may be determined. In the grid crisis state, the grid stabilizing system relaxes the control of the physical variable limits and allows them to move outside of a preferred range. In a high frequency grid state, the loads are switched on until the grid crisis state is exited and in a low frequency grid crisis state, the responsive load (e.g. fridge) is switched off until the crisis state is exited. The switching on and switching off is carried out irrespective of the control limits, so a fridge, for example, could continuously cool down to well below a preferred minimum or the fridge could be allowed to warm up to an ambient condition well above a preferred maximum temperature. These extreme measures are only taken in the most serious of grid conditions, when the alternative is a blackout.
Modeling of the prior art frequency and responsive control devices has uncovered previously unknown problems with the above described prior art grid responsive loads.
It has been found that after response has been affected for a period of time, a population of the devices will tend to approach the physical variable control limits, and start switching at an excessive rate. For example, a refrigeration unit controlled by a frequency responsive device will reach its extended temperature limits after a sustained period of high or low frequency. Using the example of a higher than nominal grid frequency, devices will switch on until the low temperature limit has been reached and will then switch off, but as soon as the temperature passes back over the low temperature limit the device will again check whether the grid frequency is above its higher frequency limits, and if so will switch on again immediately. This results in very frequent switching as the device is attempting to provide frequency response to a unit close to its physical variable limits. This is not desired behavior as it could damage the controlled loads. Excessive oscillating on and off switching of the load will reduce the lifespan of the device.
Also, modeling of the prior grid frequency responsive loads have been found to have an unexpected effect on the grid frequency. It was assumed that the responsive devices would smooth the grid frequency to provide a far clearer, less noisy, grid frequency. This did not, however, entirely bear out during modeling, and some previously unknown strange behavior of the grid frequency was observed as a result of the responsive loads.
The prior art grid responsive control devices do not provide any special assistance to a grid recovering from a blackout, but the stabilizing effect of responsive loads are needed more than ever at this time.
Amongst other objects, the present invention aims to have an improved stabilizing effect on a power grid.
The present invention also aims to reduce the switching of powering of an energy store during operation of a grid responsive device controlling the powering of the energy store.
The present invention also aims to aid the grid start-up after a blackout. In particular, the present invention aims to soften the shocks to the system during the black start process. The loads and generators can be reconnected more quickly, so speeding recovery.
The device of the present invention also aims to overcome the above identified problems with prior art grid responsive control devices.